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What It Does

CodeWeaver gives Claude and other AI agents precise context from your codebase. Not keyword grep. Not whole-file dumps. Actual structural understanding through hybrid semantic search.

You, or Claude, or your intern, can ask questions like:

• "Where do we handle OAuth tokens?"
• "Find all API endpoint definitions"
• "Show me error handling in the payment flow"

CodeWeaver returns the exact functions, classes, and code blocks — even in unfamiliar languages or massive repositories.

Example:

Without CodeWeaver:
  Claude: "Let me search for 'auth'... here are 50 files mentioning authentication"
  Result: Generic code, wrong context, wasted tokens

With CodeWeaver:
  You: "Where do we validate OAuth tokens?"
  Claude gets: The exact 3 functions across 2 files, with surrounding context
  Result: Precise answers, focused context, actual understanding

⚠️ Alpha Release: This works, but it's early. Use it, break it, help shape it.

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How CodeWeaver Stacks Up

Quick Reference Matrix

Feature	CodeWeaver	Serena	Cursor	Copilot Workspace	Sourcegraph Cody	Continue.dev	Bloop	Aider
Approach	Semantic search	Symbol lookup (LSP)	Semantic	Semantic	Keyword	Semantic	Semantic	Repo maps
Tool Count	1	20+	N/A	N/A	N/A	N/A	N/A	N/A
Prompt Overhead	~500 tokens	~16,000 tokens	N/A	N/A	N/A	N/A	N/A	N/A
Search Speed	Moderate (embeddings)	Very fast (LSP)	Moderate	Server-side	Fast	Moderate	Fast	On-demand
Embedding Providers	17	0 (no embeddings)	1-2	1	0 (deprecated)	4-5	1	0
Language Support	166+	~30 (LSP required)	~50-100	All (text)	All	~165	Unknown	~165+
Requires Language Server	❌ No	✅ Yes	❌ No	❌ No	❌ No	❌ No	❌ No	❌ No
Symbol Precision	⚠️ Semantic match	✅ Exact symbols	⚠️ Semantic	⚠️ Semantic	⚠️ Keyword	⚠️ Semantic	⚠️ Semantic	✅ Exact
Concept Search	✅ Yes	❌ Symbols only	✅ Yes	✅ Yes	⚠️ Limited	✅ Yes	✅ Yes	❌ No
Editing Capabilities	❌ No	✅ Yes (9 tools)	✅ Yes	✅ Yes	✅ Yes	✅ Yes	❌ No	✅ Yes

Notes:

• Serena tool count: Varies by context (20+ in claude-code, up to 35 total available)
• Serena prompt overhead: Measured with 21 active tools in claude-code context (~16,000 tokens)
• Language counts: CodeWeaver supports 166+ unique languages (27 with AST parsing, 139 with intelligent delimiter-based chunking)

📊 See detailed competitive analysis →

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🚀 Getting Started

Quick Install

Using the CLI with uv:

# Add CodeWeaver to your project
uv add --prerelease allow --dev code-weaver

# Initialize config and MCP setup
cw init

# Verify setup
cw doctor

# Start the server
cw server

📝 Note: cw init defaults to CodeWeaver's recommended profile:

• 🔑 Voyage AI API key (generous free tier)
• 🗄️ Qdrant instance (cloud or local, both free options)

Want full offline? Use cw init --profile quickstart for local-only operation.

🐳 Prefer Docker? See Docker setup guide →

MCP Configuration

To watch and handle your files, CodeWeaver always runs an HTTP server. You can connect to that or use your typical stdio setup:

cw init adds CodeWeaver to your project's .mcp.json:

{
  "mcpServers": {
    "codeweaver": {
      "type": "stdio",
      "cmd": "uv",
      "args": ["run", "codeweaver", "server"],
      "env": {"VOYAGE_API_KEY": "your-key-here"}
    }
  }
}

or with http:

{
  "mcpServers": {
    "codeweaver": {
      "type": "http",
      "url": "http://127.0.0.1:9328"
    }
  }
}

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✨ Features

🔍 Smart Search Hybrid search (sparse + dense vectors) AST-level understanding (27 languages) Semantic relationships Language-aware chunking (166+ languages)	🌐 Language Support 27 languages with full AST/semantic parsing 166+ languages with language-aware chunking Cross-language normalization Family heuristics for smart fallback
🔄 Resilient & Offline Full offline operation with local models Automatic failover to backup vector store Works airgapped (no cloud required) Graceful degradation with health monitoring	🔌 Provider Flexibility 17 embedding providers 50+ embedding models Sparse & dense embedding model support 5 reranking providers See full provider list →
⚙️ Configuration ~15 config sources (TOML/YAML/JSON/ENV) Cloud secret stores (AWS/Azure/GCP) Hierarchical merging Profiles for common setups	🛠️ Developer Experience Live indexing with file watching Move detection (no re-indexing duplicates) Full CLI (cw / codeweaver) Health & metrics endpoints

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💭 Philosophy

The Bigger Picture

I started building CodeWeaver because I believe AI agents need better context infrastructure. Right now:

• Agents re-read the same huge files repeatedly
• They get shallow, text-based context instead of structural understanding
• They are mostly given tools built for humans, not for how they actually work
• You don't control what context they see or how they get it

CodeWeaver addresses this with one focused capability: structural + semantic code understanding that you control and can deploy however you want.

Is this solving a big problem? We think so. But we're in alpha; we're probably not there yet. We also need real-world usage to prove it. That's where you come in. Use it, make it better. Worst case -- it's a good tool, best case -- you get better results and cut costs on AI.

📖 Read the detailed rationale →

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